Source code for ribs.emitters.opt._gradient_opt_base

"""Provides GradientOptBase."""
from abc import ABC, abstractmethod

[docs]class GradientOptBase(ABC): """Base class for gradient-based optimizers. .. note:: These optimizers are designed for gradient ascent rather than gradient descent. These optimizers maintain a current solution point :math:`\\theta`. The solution point is obtained with the :attr:`theta` property, and it is updated by passing a gradient to :meth:`step`. Finally, the point can be reset to a new value with :meth:`reset`. Your constructor may take in additional arguments beyond ``theta0`` and ``lr``, but expect that these two arguments will always be passed in. Args: theta0 (array-like): Initial solution. 1D array. lr (float): Learning rate for the update. """ def __init__(self, theta0, lr): pass @property @abstractmethod def theta(self): """The current solution point."""
[docs] @abstractmethod def reset(self, theta0): """Resets the solution point to a new value. Args: theta0 (array-like): The new solution point. 1D array. """
[docs] @abstractmethod def step(self, gradient): """Ascends the solution based on the given gradient. Args: gradient (array-like): The (estimated) gradient of the current solution point. 1D array. """